Railway disaster prevention monitoring system information grading return method

Abstract

The invention relates to the technical field of railway disaster prevention monitoring wireless communication, in particular to a railway disaster prevention monitoring system information grading return method. According to the method, edge-side preprocessing and feature grading are performed on monitoring data by fully utilizing the computing power of disaster prevention monitoring nodes, and a state-driven information return strategy is adopted for safety-related abnormal information, so the real-time performance of return of the safety-related information is ensured; for data information in a normal state, according to the state of the disaster prevention monitoring node, a variable-period information return strategy is adopted, and the periodical integrity of conventional information return is ensured. By combining the advantages of two information return strategies of state driving and variable period, on the premise of ensuring the real-time transmission of safety related information, the energy and bandwidth resource waste caused by redundant information return is effectively reduced, and the life cycle and service capability of the monitoring system are improved.

Description

technical field [0001] The invention relates to the technical field of wireless communication for railway disaster prevention monitoring, in particular to a method for graded return transmission of railway disaster prevention monitoring system information. Background technique [0002] With the rapid increase in operating speed and rapid growth in operating mileage, railways have become one of the main ways for passengers to travel and express freight in China, and are an important pillar of my country's national economic and social development. However, my country's railway lines cover a wide area and the operating environment is complex and changeable, which poses great challenges to the safety and reliability of the railway system operation. Technologies such as real-time acquisition, transmission, and calculation of disaster-causing factor information play an increasingly important role in railway disaster prevention and control, providing rich big data support and effec...

AI Technical Summary

Problems solved by technology

[0003] At present, most of the disaster prevention monitoring data along the railway line use a fixed sampling frequency for data perception and transmission, which can maintain the integrity of the monitoring data return to the greatest extent, but the sampling frequency of this transmission method has a decisive effect on the monitoring effect

On the one hand, a large sampling frequency will increase the amount of redundant data transmission and the corresponding waste of energy resources; Security risks

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